Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid disease predictions. A systematic literature review (SLR) strategy is used in this study to give a comprehensive overview of the existing literature on forecasting data on thyroid disease diagnosed using ML. This study includes 168 articles published between 2013 and 2022, gathered from high-quality journals and applied meta-analysis. The thyroid disease diagnoses (TDD) category, techniques, applications, and solutions were among the many elements considered and researched when reviewing the 41 articles of cited literature used in this research. According to our SLR, the current technique's actual application and efficacy are constrained by several outstanding issues associated with imbalance. In TDD, the technique of ML increases data-driven decision-making. In the Meta-analysis, 168 documents have been processed, and 41 documents on TDD are included for observation analysis. The limits of ML that are discussed in the discussion sections may guide the direction of future research. Regardless, this study predicts that ML-based thyroid disease detection with imbalanced data and other novel approaches may reveal numerous unrealised possibilities in the future
Background: Diabetes is a metabolic disorder characterized by chronic hyperglycemia due to an inability to produce insulin. Uncontrolled or poorly controlled diabetes is clinically associated with increased susceptibility to delay healing. Many recent researches have shown that stem cell therapy can be the best choice for treatment of this disease. The aims of this research were investigating regeneration of pancreatic beta cells of diabetic induced rabbits after stem cell transplantation. Materials and Methods: 64 rabbits weighting an average of (2.5 - 3 kg) were used in this experimental study, and divided into 4 groups as follows; group A ( contains 16 healthy rabbits regarded as control group ) , Group B ( contains 16 diabetic rabbits
... Show MoreCancer stay to be one of the leading causes of death throughout the world due to a limited success to use treatments. The new synthesized metal complexes with formula: [Ni L2 (H2O)2]. 2.5 E t OH and [Cd L2]. ½ H2O Where L = Bis [ 5 – ( P – nitrophenyl ) - 4 – phenyl 1 , 2 , 4 – trazol – 3 – dithiocarbamato hydrazide ] and the aqueous extract of Teucrium polium L.(TP) plant (Ja,adahin Arabic) were examined against growth cells of hepatocellular Carcinoma cell Line ( HeP2 ). The cytotoxicity assay of cancer cell line was used for determination of inhibition rate with three concentrations; (62.5, 105 and 250 µg /200µl). The aqueous extract of TP plant induced death of cancer cells by significant elevation of the inhib
... Show MoreThe Reasons behind the decadence of the studies concerning the evening school in Salah al Deen A field study
This study is an approach to assign the land area of Kirkuk city [ a city located in the northern of Iraq, 236 kilometers north of Baghdad and 83 kilometers south of Erbil [ Climatic atlas of Iraq, 1941-1970 ] into different multi zones by using Satellite image and Arc Map10.3, zones of different traffic noise pollutions. Land zonings process like what achieved in this paper will help and of it’s of a high interest point for the future of Kirkuk city especially urban
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This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per
... Show MoreThermomechanical analysis (TMA) and differential scanning calorimetry (DSC) are used to investigate the effect of molding and annealing of polyester on the behavior of thermal expansion and crystallization since these factors play role in the reprocessing or recycling of the polymer. The dynamic mode of the TMA provides enhanced characterization information about the polyester since it separates the transitions into reversible and irreversible signals, and also reveals the progress of the amorphous regions as the polyester loses strength with the increasing temperature approaching melting. Slow cooling after annealing brings crystallization that may be attributed to molecular chain straightening due to orientation.
The field of autonomous robotic systems has advanced tremendously in the last few years, allowing them to perform complicated tasks in various contexts. One of the most important and useful applications of guide robots is the support of the blind. The successful implementation of this study requires a more accurate and powerful self-localization system for guide robots in indoor environments. This paper proposes a self-localization system for guide robots. To successfully implement this study, images were collected from the perspective of a robot inside a room, and a deep learning system such as a convolutional neural network (CNN) was used. An image-based self-localization guide robot image-classification system delivers a more accura
... Show MoreA laboratory experiment was conducted in the labs of Seeds Testing and Certification Department, Ministry of Agriculture in 2017 to improve germination and seedling growth in primed sorghum seeds by different concentrations and soaking durations of acids of gibberellic (GA3)(distilled water, 75, 150 and 300 mg l-1), salicylic (SA)(distilled water, 40, 70 and 100 mg l-1) and soaking duration (SD)(12 and 24 h). Factorial experiment in completely randomized design was applied with four r replications. The results showed the superiority of the two soaking treatments with GA3 (300 mg l-1) and SA (70 mg l-1) at germination ratio, radicle and plumule lengths, seedling dry weight and seedling vigour index (81.3%, 2.7 cm, 8.9 cm, 0.081 mg and 984) a
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